Application in Medical Imaging
Hardback 256 pp.
The advent of digital imaging technologies such as MRI has revolutionized modern medicine. With the wide-spread use of digital imaging in medicine today, the quality of digial medical images becomes an important issue. To achieve the best possible diagnoses it is important that medical images be sharp, clear, and free of noise. While the technologies for acquiring digital medical images continue to improve, resulting in images of higher and higher resolution and quality, noise remains an issue for many medical images. Removing noise in these digital images remains one of the major challenges in the study of medical imaging.
Wavelets have been used for compact signal and image representations in denoising, compression and feature detection processing problems for about twenty years.
Instead of trying to replace standard image processing techniques, wavelet transforms offer an efficient representation of the signal, finely tuned to its intrinsic properties and can accomplish remarkable performance and efficiency for many image processing problems.
About the Authors
Abdeldjalil Ouahabi is Professor and Director of Polytech’Tours’s Signal & Image Group. He is currently Deputy Director for International Relations at Polytech’Tours (Ecole Polytechnique de l’Université de Tours). His main research area is image and signal processing. He has a strong interest in sampling theories multiresolution algorithms, optimal filtering, spectral analysis, wavelets, and the use of fractals for image processing. He is the author of over 100 published papers in these areas.